Memristive devices are electrical resistance switches that can retain a state of internal resistance based on the history of applied voltage and current. These devices can store and process information, and offer several key performance characteristics that exceed conventional integrated circuit technology. An important class of memristive devices are two-terminal resistance switches based on ionic motion, which are built from a simple conductor/insulator/conductor thin-film stack. These devices were originally conceived in the late 1960s and recent progress has led to fast, low-energy, high-endurance devices that can be scaled down to less than 10 nm and stacked in three dimensions. However, the underlying device mechanisms remain unclear, which is a significant barrier to their widespread application. Here, we review recent progress in the development and understanding of memristive devices. We also examine the performance requirements for computing with memristive devices and detail how the outstanding challenges could be met.

Memristive devices for computing

Numerous candidates attempting to replace Si-based flash memory have failed for a variety of reasons over the years. Oxide-based resistance memory and the related memristor have succeeded in surpassing the specifications for a number of device requirements. However, a material or device structure that satisfies high-density, switching-speed, endurance, retention and most importantly power-consumption criteria has yet to be announced. In this work we demonstrate a TaO(x)-based asymmetric passive switching device with which we were able to localize resistance switching and satisfy all aforementioned requirements. In particular, the reduction of switching current drastically reduces power consumption and results in extreme cycling endurances of over 10(12). Along with the 10 ns switching times, this allows for possible applications to the working-memory space as well. Furthermore, by combining two such devices each with an intrinsic Schottky barrier we eliminate any need for a discrete transistor or diode in solving issues of stray leakage current paths in high-density crossbar arrays.

A fast, high-endurance and scalable non-volatile memory device made from asymmetric Ta2O5−x/TaO2−x bilayer structures

The accumulation and extrusion of Ca2+ in the pre- and postsynaptic compartments play a critical role in initiating plastic changes in biological synapses. To emulate this fundamental process in electronic devices, we developed diffusive Ag-in-oxide memristors with a temporal response during and after stimulation similar to that of the synaptic Ca2+ dynamics. In situ high-resolution transmission electron microscopy and nanoparticle dynamics simulations both demonstrate that Ag atoms disperse under electrical bias and regroup spontaneously under zero bias because of interfacial energy minimization, closely resembling synaptic influx and extrusion of Ca2+, respectively. The diffusive memristor and its dynamics enable a direct emulation of both short- and long-term plasticity of biological synapses, representing an advance in hardware implementation of neuromorphic functionalities.

/pdf/memristors-with-diffusive-dynamics-as-synaptic-emulators-for-4j06bmhu3f.pdf

Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing

A memristor is a resistive device with an inherent memory. The theoretical concept of a memristor was connected to physically measured devices in 2008 and since then there has been rapid progress in the development of such devices, leading to a series of recent demonstrations of memristor-based neuromorphic hardware systems. Here, we evaluate the state of the art in memristor-based electronics and explore where the future of the field lies. We highlight three areas of potential technological impact: on-chip memory and storage, biologically inspired computing and general-purpose in-memory computing. We analyse the challenges, and possible solutions, associated with scaling the systems up for practical applications, and consider the benefits of scaling the devices down in terms of geometry and also in terms of obtaining fundamental control of the atomic-level dynamics. Finally, we discuss the ways we believe biology will continue to provide guiding principles for device innovation and system optimization in the field. This Perspective evaluates the state of the art in memristor-based electronics and explores the future development of such devices in on-chip memory, biologically inspired computing and general-purpose in-memory computing.

The future of electronics based on memristive systems

Modern computers are based on the von Neumann architecture in which computation and storage are physically separated: data are fetched from the memory unit, shuttled to the processing unit (where computation takes place) and then shuttled back to the memory unit to be stored. The rate at which data can be transferred between the processing unit and the memory unit represents a fundamental limitation of modern computers, known as the memory wall. In-memory computing is an approach that attempts to address this issue by designing systems that compute within the memory, thus eliminating the energy-intensive and time-consuming data movement that plagues current designs. Here we review the development of in-memory computing using resistive switching devices, where the two-terminal structure of the devices, their resistive switching properties, and direct data processing in the memory can enable area- and energy-efficient computation. We examine the different digital, analogue, and stochastic computing schemes that have been proposed, and explore the microscopic physical mechanisms involved. Finally, we discuss the challenges in-memory computing faces, including the required scaling characteristics, in delivering next-generation computing. This Review Article examines the development of in-memory computing using resistive switching devices.

/pdf/in-memory-computing-with-resistive-switching-devices-1mv368csjy.pdf

In-memory computing with resistive switching devices

On the road towards higher memory density and computer performance, a significant improvement in energy efficiency constitutes the dominant goal in future information technology. Passive crossbar arrays of memristive elements were suggested a decade ago as non-volatile random access memories (RAM) and can also be used for reconfigurable logic circuits. As such they represent an interesting alternative to the conventional von Neumann based computer chip architectures. Crossbar architectures hold the promise of a significant reduction in energy consumption because of their ultimate scaling potential and because they allow for a local fusion of logic and memory, thus avoiding energy consumption by data transfer on the chip. However, the expected paradigm change has not yet taken place because the general problem of selecting a designated cell within a passive crossbar array without interference from sneak-path currents through neighbouring cells has not yet been solved satisfactorily. Here we introduce a complementary resistive switch. It consists of two antiserial memristive elements and allows for the construction of large passive crossbar arrays by solving the sneak path problem in combination with a drastic reduction of the power consumption.

Complementary resistive switches for passive nanocrossbar memories

Redox-based nanoionic resistive memory cells are one of the most promising emerging nanodevices for future information technology with applications for memory, logic and neuromorphic computing. Recently, the serendipitous discovery of the link between redox-based nanoionic-resistive memory cells and memristors and memristive devices has further intensified the research in this field. Here we show on both a theoretical and an experimental level that nanoionic-type memristive elements are inherently controlled by non-equilibrium states resulting in a nanobattery. As a result, the memristor theory must be extended to fit the observed non-zero-crossing I-V characteristics. The initial electromotive force of the nanobattery depends on the chemistry and the transport properties of the materials system but can also be introduced during redox-based nanoionic-resistive memory cell operations. The emf has a strong impact on the dynamic behaviour of nanoscale memories, and thus, its control is one of the key factors for future device development and accurate modelling.

/pdf/nanobatteries-in-redox-based-resistive-switches-require-1s2m5t603y.pdf

Nanobatteries in redox-based resistive switches require extension of memristor theory

The realization of logic operations within passive crossbar memory arrays is a promising approach to expand the fields of application of such architectures. Material implication was recently suggested as the basic function of memristive crossbar junctions, and single bipolar resistive switches (BRS) as well as complementary resistive switches (CRS) were shown to be capable of realizing this logical functionality. Based on a systematic analysis of the Boolean functions, we demonstrate here that 14 of 16 Boolean functions can be realized with a single BRS or CRS cell in at most three sequential cycles. Since the read-out step is independent of the logic operation steps, the result of the logic operation is directly stored to memory, making logic-in-memory applications feasible.

https://iopscience.iop.org/article/10.1088/0957-4484/23/30/305205/pdf

Beyond von Neumann—logic operations in passive crossbar arrays alongside memory operations

Realization of logic and storage operations in memristive circuits have opened up a promising research direction of in-memory computing. Elementary digital circuits, e.g., Boolean arithmetic circuits, can be economically realized within memristive circuits with a limited performance overhead as compared to the standard computation paradigms. This paper takes a major step along this direction by proposing a fully-programmable in-memory computing system. In particular, we address, for the first time, the question of controlling the in-memory computation, by proposing a lightweight unit managing the operations performed on a memristive array. Assembly-level programming abstraction is achieved by a natively-implemented majority and complement operator. This platform enables diverse sets of applications to be ported with little effort. As a case study, we present a standardized symmetric-key cipher for lightweight security applications. The detailed system design flow and simulation results with accurate device models are reported validating the approach.

The Programmable Logic-in-Memory (PLiM) computer

Emerging resistively switching devices are thought to enable ultradense passive nanocrossbar arrays for use as random access memories (ReRAM) by the end of the decade, both for embedded and mass storage applications. Moreover, ReRAMs offer inherent logic-in-memory (LIM) capabilities due to the nonvolatility of the devices and therefore great potential to reduce the communication between memory and calculation unit by alleviating the so-called von Neumann bottleneck. A single bipolar resistive switching device is capable of performing 14 of 16 two input logic functions in the logic concept presented by Linn et al. (“CRS-logic”). In this paper, five types of selectorless devices are considered to validate this CRS-logic concept is experimentally by means of the IMP and AND logic operations. As reference device a TaO x -based ReRAM cell is considered, which is compared to three more advanced device configurations consisting either of a threshold supported resistive switch (TS-ReRAM), a complementary switching device (CS), or a complementary resistive switch (CRS). It is shown that all of these devices offer the desired LIM behavior. Moreover, the feasibility of XOR and XNOR operations using a modified logic concept is applied for both CS and CRS devices and the pros and cons are discussed.

Eike Linn

Papers

Complementary resistive switches for passive nanocrossbar memories

Nanobatteries in redox-based resistive switches require extension of memristor theory

Beyond von Neumann—logic operations in passive crossbar arrays alongside memory operations

The Programmable Logic-in-Memory (PLiM) computer

Realization of Boolean Logic Functionality Using Redox‐Based Memristive Devices